A method to estimate synaptic conductances from membrane potential
Michael Rudolph, Zuzanna Piwkowska, Mathilde Badoual, Thierry Bal
and Alain Destexhe.
Journal of Neurophysiology 91: 2884-2896, 2004.
In neocortical neurons, network activity can activate a large number
of synaptic inputs, resulting in highly irregular subthreshold
membrane potential (Vm) fluctuations, commonly called ``synaptic
noise''. This activity contains information about the underlying
network dynamics, but it is not easy to extract network properties
from such complex and irregular activity. Here, we propose a method
to estimate properties of network activity from intracellular
recordings and test this method using theoretical and experimental
approaches. The method is based on the analytic expression of the
subthreshold Vm distribution at steady-state in conductance-based
models. Fitting this analytic expression to Vm distributions
obtained from intracellular recordings provides estimates of the mean
and variance of excitatory and inhibitory conductances. We test the
accuracy of these estimates against computational models of
increasing complexity. We also test the method using dynamic-clamp
recordings of neocortical neurons in vitro. By using an
on-line analysis procedure, we show that the measured conductances
from spontaneous network activity can be used to recreate artificial
states equivalent to real network activity. This approach should be
applicable to intracellular recordings during different network
states in vivo, providing a characterization of the global
properties of synaptic conductances and possible insight on the
underlying network mechanisms.
An Editorial focus has been written about this article:
A. Korngreen, Noise in the foreground. Journal of
Neurophysiology 91: 2400, 2004.
PDF copy of this Editorial focus
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